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Scattering identification ambiguity has significant effects in the polarimetric SAR (Synthetic Aperture Radar) decomposition and can be reduced by discriminating the permanent and time-varying features using PolInSAR (Polarimetric SAR Interferometry) coherence. PolInSAR based polarimetric decomposition using cosine-squared distribution (PCSD decomposition) is an algorithm that demonstrates the incorporation of PolInSAR coherence in the decomposition model by assuming the distribution of forest structure and vegetation as cosine-squared. This study presents a multifrequency analysis of PCSD decomposition to evaluate its potential to rightly represent the scatterer by reducing the identification ambiguity. The false-color composites (FCC) of PCSD decomposed images are presented to examine the results. A comparison study is also conducted between the PCSD decomposition and the Yamaguchi-4 component (Y4C) decomposition to demonstrate the improvement in the representation of the ground targets. [ABSTRACT FROM AUTHOR]